Massive-MIMO (M-MIMO) allows to schedule users with high gain narrow beams and to reduce intra-cell inter-beam interference. Close to cell edge, users may experience high interference from beams of neighboring cells which degrades their performance. This paper introduces low complexity inter-cell interference coordination between neighboring cells for M-MIMO systems implementing Grid of Beams (GoB) using Radio Environment Maps (REMs). The REMs are designed using the Kriging with the Covariance Tapering spatial interpolation technique and are created for the serving and the interfering beams. The interference coordination is introduced as constraints to the schedulers that avoid simultaneous scheduling of users served by highly interfering beams from the neighboring cells. The coordination decision is based on information retrieved from REMs and its quality depends on the REMs’ precision. Around 72 percent performance gain in terms of mean user throughput is achieved by the REM based coordination with respect to a baseline solution without coordination, and around 40 percent gain with respect to a state of the art solution that implements coordination using information at beam level resolution.

The automatic modulation identification of a detected signal represents an essential task for an intelligent receiver and plays an important role in demodulating the intercepted signals for several communication systems. In this study, the authors propose an efficient algorithm of superposed modulations identification dedicated for two‐way relaying multiple‐input multiple‐output systems with physical‐layer network coding (PLNC). The aim of this work is to identify a pair of sources modulations from the superposed constellation, when PLNC is applied. For this purpose, the authors use the higher order statistics‐based features in conjunction with genetic algorithm and information theory as a features selection method and the random forests as a classifier. Simulations are provided to assess the accuracy of the proposed algorithm through the average probability of correct identification for different modulation scheme pairs. It is shown that the algorithm achieves high‐modulation identification in acceptable signal‐to‐noise ratio level at different relay position.